Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 121 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
2. 2.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
3. 3.Which of these is bad for training a model? (a) copies of one photo (b) correct labels (c) photos in many lights (d) many varied examples
4. 4.🔍 Which is the odd one out? (a) labels added at random (b) checking labels twice (c) photos in many lights (d) clear, sharp examples
5. 5.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
6. 6.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
7. 7.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) copies of one photo (d) many varied examples
8. 8.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) only one kind of example (d) clear, sharp examples
9. 9.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
10. 10.True or false: “labels added at random” is good for training a model. (a) True (b) False
11. 11.🔍 Which is the odd one out? (a) only one kind of example (b) many varied examples (c) clear, sharp examples (d) new data for testing
12. 12.Which of these is bad for training a model? (a) many varied examples (b) blurry, unclear photos (c) examples of every type (d) photos in many lights
13. 13.True or false: “labels added at random” is bad for training a model. (a) False (b) True
14. 14.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
15. 15.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) forget everything (d) slower to switch on
16. 16.True or false: “many varied examples” is bad for training a model. (a) True (b) False
17. 17.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will be perfect (d) it will turn yellow
18. 18.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) copies of one photo (d) clear, sharp examples
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
21. 21.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
22. 22.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) new data for testing (d) wrong labels
23. 23.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
24. 24.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
25. 25.🔍 Which is the odd one out? (a) clear, sharp examples (b) very few examples (c) examples of every type (d) checking labels twice
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
27. 27.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
28. 28.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
29. 29.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
30. 30.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
31. 31.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) photos in many lights (d) very few examples
32. 32.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) photos in many lights (d) wrong labels
33. 33.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
34. 34.🔍 Which is the odd one out? (a) examples of every type (b) photos in many lights (c) checking labels twice (d) testing on training data
35. 35.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
36. 36.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) correct labels (d) only one kind of example
37. 37.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
38. 38.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
39. 39.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
40. 40.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) photos in many lights (d) labels added at random

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